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Fluid Dynamics and Mixing

Fluid Dynamics and Mixing is a research topic within Biomedical Engineering. Science Explorer counts 24k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on bioreactor scale-up, oxygen transfer, and mixing efficiency in microbial processes. It covers topics such as bubble column reactors, CFD simulation, fungal morphology, and mass transfer coefficients in turbulent flows.

  • Bioreactor
  • Scale-up
  • Oxygen Transfer
  • Microbial Processes
  • Bubble Column Reactors
  • Mixing Efficiency
  • CFD Simulation
  • Fungal Morphology
  • Mass Transfer Coefficients
  • Turbulent Flows
Research works
24k
fractional, since 1950
In the world top 10%
2.3k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+4%
the tick is no change
Largest producer
China
52% of the 10 largest, 2022-now

Which countries lead Fluid Dynamics and Mixing research?

By volume, China and the United States publish the most (1.5k and 319 works in 2022-now).

By volume, 2022-now

  1. 1 China 1.5k works
  2. 2 United States 319 works
  3. 3 India 205 works
  4. 4 Germany 182 works
  5. 5 Japan 158 works
  6. 6 France 139 works
  7. 7 Russia 134 works
  8. 8 United Kingdom 108 works
  9. 9 Canada 85 works
  10. 10 Brazil 81 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 51.6%United States: 11.0%India: 7.0%Germany: 6.2%6 others listed: 24.2%52%largest
China1,503 · 51.6%United States319 · 11.0%India205 · 7.0%Germany182 · 6.2%6 others listed704 · 24.2%

Shares of the rows listed above, not of the whole node.

Which institutions lead Fluid Dynamics and Mixing research?

By volume in 2022-now, Tianjin University publishes the most Fluid Dynamics and Mixing research, followed by Centre National de la Recherche Scientifique and Russian Academy of Sciences.

Who are the leading researchers in Fluid Dynamics and Mixing?

The most-cited researchers publishing on Fluid Dynamics and Mixing include Reza Malekzadeh, George M. Whitesides and Kai You Wang.

  1. 1 Reza Malekzadeh Iran 278k citations
  2. 2 George M. Whitesides United States 267k citations
  3. 3 Kai You Wang China 224k citations
  4. 4 Lei Jiang China 214k citations
  5. 5 Patrick W.J.C. Serruys Netherlands 206k citations
  6. 6 David Julian McClements United States 185k citations
  7. 7 Qiang Zhang China 184k citations
  8. 8 Jacob Cohen Israel 170k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Fluid Dynamics and Mixing?

The most cited paper in Fluid Dynamics and Mixing is "A model for predicting flow regime transitions in horizontal and near horizontal gas‐liquid flow" (Yemada Taitel, Abe E. Dukler, 1976), with 2,923 citations. Next come "Average Volumetric Concentration in Two-Phase Flow Systems" (2,511) and "Drag coefficient and relative velocity in bubbly, droplet or particulate flows" (2,035).

Most cited papers
#PaperReleasedCitations
1 A model for predicting flow regime transitions in horizontal and near horizontal gas‐liquid flow Yemada Taitel, Abe E. Dukler · AIChE Journal 1976 2,923
2 Average Volumetric Concentration in Two-Phase Flow Systems Novak Zuber, J. A. Findlay · ASME Journal of Heat and Mass Transfer Nov 1965 2,511
3 Drag coefficient and relative velocity in bubbly, droplet or particulate flows Mamoru Ishii, Novak Zuber · AIChE Journal Sep 1979 2,035
4 Turbulent Dispersed Multiphase Flow S. Balachandar, John K. Eaton · Annual Review of Fluid Mechanics Review 2010 1,775
5 Modelling flow pattern transitions for steady upward gas‐liquid flow in vertical tubes ‪Yehuda Taitel, Dvora Barnea, Abe E. Dukler · AIChE Journal May 1980 1,754
All 100 most cited papers, with filters and sorting

Where is Fluid Dynamics and Mixing research done?

The largest centres of Fluid Dynamics and Mixing research in 2022-now are Beijing (China), Shanghai (China), Tianjin (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Dresden and Xuzhou.

Largest cities, 2022-now

  1. 1 BeijingChina 307 works
  2. 2 ShanghaiChina 115 works
  3. 3 TianjinChina 101 works
  4. 4 Xi'anChina 92 works
  5. 5 HangzhouChina 72 works
  6. 6 ChengduChina 60 works
  7. 7 QingdaoChina 57 works
  8. 8 TokyoJapan 51 works
  9. 9 ChongqingChina 47 works
  10. 10 HarbinChina 44 works

Where it is the local speciality

  1. DresdenDE · 41.0 works13×
  2. XuzhouCN · 33.0 works9.5×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Fluid Dynamics and Mixing than the world average.

See Fluid Dynamics and Mixing on the map

Where is the best place to study Fluid Dynamics and Mixing?

Among universities, judged by research, City University of Hong Kong, University of Newcastle Australia and China University of Mining and Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 17.7%fractional works in this field (log) →share of work in the world top 10% →University of Newcas…City University of H…China University of …Xi'an Jiaotong Unive…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1City University of Hong KongChina 74.221.9%13.2×25 +503.2%
2University of Newcastle AustraliaAustralia 68.133.4%12.3×10 +21.5%
3China University of Mining and TechnologyChina 65.620.0%12.4×32 +37.7%
4Xi'an Jiaotong UniversityChina 61.617.8%9.1×52 +6.0%
5Tianjin UniversityChina 59.77.1%19.3×78 +25.0%
6Toronto Metropolitan UniversityCanada 55.814.0%17.2×12 +43.0%
7Tsinghua UniversityChina 55.114.3%5.3×40 +17.2%
8King Fahd University of Petroleum and MineralsSaudi Arabia 54.720.4%11.0×12 +31.3%
9Shanghai Jiao Tong UniversityChina 54.510.0%5.2×49 +107.6%
10Kunming University of Science and TechnologyChina 53.518.1%11.9×22 +317.5%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Fluid Dynamics and Mixing, country by country

Is Fluid Dynamics and Mixing research growing?

Output in 2022-2025 was 4% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Fluid Dynamics and Mixing.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Fluid Dynamics and Mixing as a percentage of every work published that year, 0.016% in 2024.

still counting0.020%0.040%Fluid Dynamics and Mixing0.016% in 202519801990200020102020

Fractional works of Fluid Dynamics and Mixing over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Fluid Dynamics and Mixing10.1% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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